Panel facilitated during the Insurance Market Summit 2018 in Hartford, Connecticut

1. 11.29.18
Automation, Analytics & Artificial Intelligence:
Opportunities, Risks, and Challenges
Dr Anand S. Rao, Global AI Lead, PwC

2. PwC’s Digital Services
Our world is rapidly changing...
64% of executives believe technology will disrupt how
they do business in next 5 years.
—PwC
Source: PwC’s 21st Annual Global CEO Survey (2018)
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3. Enterprises are realizing the value from digitization to AI along two distinct but
related paths, to enhance productivity, increase profits and enhance experience
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Digitization
Artificial Intelligence
Productivity Experience Profits
Simplification
Standardization
Automation
Decision-making
Personalization
Analytics
Revenues
AutomationPath
AnalyticsPath

4. Automation Path: Enterprises are moving from BPA to IPA to fully
exploit AI, enhance productivity and reduce costs of operation
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Macros and Scripts
Rules-based automation within a
specific application (e.g., Excel)
to provide users with a way to
automate a repeatable process
with highly structured data
Business Process
Automation (BPA)
Reengineering existing business
processes by using software,
integrating systems, and
restructuring labor to optimize
workflows and minimize costs
Robotic Process Automation
(RPA)
Alias: Robotic Desktop
Automation (RDA)
Automating labor-intensive,
repetitive activities across
multiple systems and interfaces
by training and/or programming
third-party software to replicate a
user’s workflow
Operates at the presentation layer
without the need to change
existing systems
Intelligent Process
Automation (IPA)
Aliases: Cognitive Computing,
Smart Workflows
Combining RPA with artificial
intelligence technologies to
identify patterns, learn over time,
and optimize workflows
Through “supervised” and
“unsupervised” learning,
algorithms make predictions and
provide insights on recognized
patterns
Algorithmic Business
Industrialized use of complex
mathematical algorithms to drive
improved business decisions or
process automation for
competitive differentiation
How do RPA and IPA
differ?
RPA directly mimics
human behavior
IPA learns how to become
more efficient
ProgramInput Output
ProgramInput
Learning
Output

5. Analytics Path: Enterprises are moving from descriptive analytics to
cognitive analytics to fully exploit AI, enhance experience and improve margins
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Describe, summarize
and analyze historical
data
Recommend ‘right’
or optimal actions
or decisions
Monitor, decide,
and act
autonomously or
semi-autonomously
Predict future
outcomes based
on facts from the
past and
simulations
Descriptive
Predictive
Prescriptive
Cognitive
Identify causes of
trends and
outcomes
Diagnostic
(What
happened?)
(Why it
happened?)
(What could
happen?)
(What should be
done?)
(How do we
adapt to change?)

6. Four ways that AI is used in enterprises:
No human in the loopHuman in the loop
Hardwired /
specific
systems
Adaptive
systems
Automated Intelligence
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Assisted Intelligence
2
Augmented Intelligence
3
Autonomous Intelligence
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+
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7. Statistics Econometrics Optimization
Complexity
Theory
Computer
Science
Game
Theory
FOUNDATION LAYER 7
AI that can act…
▪ Robotic process automation
▪ Deep question & answering
▪ Machine translation
▪ Collaborative systems
▪ Adaptive systems
AI that can sense…
▪ Natural language
▪ Audio & speech
▪ Machine vision
▪ Navigation
▪ Visualization
AI is defined as the theory and development of systems that sense the environment,
make decisions, and act that would normally require human intelligence.
Hear
See
Speak
Feel
AI that can think…
▪ Knowledge & representation
▪ Planning & scheduling
▪ Reasoning
▪ Machine Learning
▪ Deep Learning
Physical
Creative
Cognitive
Reactive
Understand
Perceive
Plan
Assist

8. AI will contribute to substantial gains in productivity and consumption.
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Are you ready to exploit the opportunities from
AI & overcome the challenges?
Global GDP Impact of AI through 2030
GlobalGDPupliftduetoAI
($intrillions)
2030 IMPACT:
$15.7T
Consumption
Contribution:
60%
Source: PwC Global Artificial Intelligence Study, 2017-2018
Productivity
Contribution:
40%

9. Operations & DevelopmentOutbound Logistics
Insurers carry out a huge number of activities and make countless decisions
across the value chain that are being optimized or disrupted by AI
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Product
Development
Service &
Support
Underwriting &
Operations
Sales &
Distribution
Customers &
Marketing
Strategy &
Growth
Risk, Finance,
Capital
Claims
Inbound Logistics
How do we efficiently manage
our capital and get better ROE?
Director, Finance
How can we engage with our
customers to enhance their
experience?
Director, Marketing
How can we grow our market
share and which markets to
enter, exit or expand?
Director, Strategy
How do we innovate and
introduce new products and
services?
Director, Products
How do we increase customer
satisfaction and retain more
customers?
Director, Service
How can we reach more
customers and price our
products to increase sales?
Director, Sales
How can we streamline
underwriting and enhance
efficiencies of our operations?
Director, Underwriting,
Operations
How can we balance losses,
claims experience and claims
costs?
Director, Claims
• Market Share
• Customer Experience
• Acquisition Rate
• Innovation Rate
• Operational Efficiency
• Customer Satisfaction
• Expense Ratio
• Claims Ratio
Over 300+ AI Use Cases Across 8 Sectors – Sizing the Prize

10. 10
Robo-advisor for financial
wellness
What’s the situation?
RIIA wanted to highlight the household balance
sheet and new ways of planning for retirement
income, but was stuck with traditional portfolio
optimization models
What we did…
We built consumer and household level ‘digital
twins’ using synthetic datasets and agent-based
simulation
What were the benefits?
Gamification of Strategy resulted in the
development of a digital advisor that simulates
household level (128 million) financial data into the
future to enhance financial wellness
Customer Experience

11. Modeling a futuristic robo-
taxi ridesharing fleet.
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TEMPLATE B SAMPLE
“Autonomous vehicles are among the client’s
highest priorities. The modeling has had a
significant impact on how they think and plan.”
ANAND RAO
PwC Artificial Intelligence Leader
What’s the situation?
GM recognized the need to invest in alternative
transportation services, but needed to understand
what services could be profitable and how they
should be operated.
What we did…
We built a dynamic simulation to identify drivers
of adoption and optimal operational structures.
What were the benefits?
We performed a scenario analysis with more than
200,000 go-to-market scenarios to identify target
markets, as well as launch and operations
strategies.
Designing New Markets

12. PwC 12
Balance the opportunities with the significant risks that need to be assessed,
mitigated and managed
Control
• Risk of AI going ‘rogue’
(e.g., Tay Chatbot)
• Inability to control
malevolent AI
• Swarm drones
Security
• Cyber intrusion risks
• Privacy risks
• Open source software risks
• Digital, Physical, Political security
Societal
• Risk of Autonomous
Weapons proliferation
• Risk of ‘intelligence divide’
Ethical
• ‘Lack of Values’ risk
• Value Alignment risk
• Goal Alignment risk Economic
• Job displacement risks
• ‘Winner-takes-all’ concentration of
power risk
• Liability risk
Performance
• Risk of Errors
• Risk of Bias
• Risk of Opaqueness
• Risk of stability of performance
• Lack of feedback process
Risk
Robust &
Safe AI
Beneficial
AI
Responsible AI

13. Six success
factors to help
you derive
maximum
benefits from AI.
Start from
business decisions
No.1
Demonstrate value
through pilots
before scaling
No.2
Blend intuition and
data-driven insights
No.3
Address ‘big data’ –
don’t forget ‘lean’ data
No.4
Fail forward –
test and learn culture
No.5
Focus on Responsible
AI from the start
No.6
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14. PwC’s Digital Services
Automation, Analytics, and Artificial Intelligence are
rewiring how we work, think, and live.
Whether you lead or follow,
start exploring.
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